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alphaear-predictor

Market prediction skill using Kronos. Use when user needs finance market time-series forecasting or news-aware finance market adjustments.

Published by RKiding ↗RKiding/Awesome-finance-skills

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alphaear-predictor

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Use alphaear-predictor to forecast [ticker] for [forecast horizon], using a trusted configured Kronos model and embedding model, then return the technical forecast and a news-aware adjusted JSON forecast.

Required inputs

  • [ticker]
  • [forecast horizon]

User-approved starter prompt based on a pinned source version; check current skill requirements before running. Task evidence ↗

SKILL.md

name: alphaear-predictordescription: Market prediction skill using Kronos. Use when user needs finance market time-series forecasting or news-aware finance market adjustments.

AlphaEar Predictor Skill

Overview

This skill utilizes the Kronos model (via KronosPredictorUtility) to perform time-series forecasting and adjust predictions based on news sentiment.

Capabilities

1. Forecast Market Trends

1. Forecast Market Trends

Workflow:

  1. Generate Base Forecast: Use scripts/kronos_predictor.py (via KronosPredictorUtility) to generate the technical/quantitative forecast.
  2. Adjust Forecast (Agentic): Use the Forecast Adjustment Prompt in references/PROMPTS.md to subjectively adjust the numbers based on latest news/logic.

Key Tools:

  • KronosPredictorUtility.get_base_forecast(df, lookback, pred_len, news_text): Returns List[KLinePoint].

Example Usage (Python):

from scripts.utils.kronos_predictor import KronosPredictorUtility
from scripts.utils.database_manager import DatabaseManager

db = DatabaseManager()
predictor = KronosPredictorUtility()

# Forecast
forecast = predictor.predict("600519", horizon="7d")
print(forecast)

Configuration

This skill requires the Kronos model and an embedding model.

  1. Kronos Model:
    • Ensure exports/models directory exists in the project root.
    • Place trained news projector weights (e.g., kronos_news_v1.pt) in exports/models/.
    • Or depend on the base model (automatically downloaded).

[!CAUTION] Model Security: This skill loads model weights from exports/models. We use weights_only=True and only scan for the kronos_news_*.pt pattern. Ensure you only place trusted checkpoints in this directory.

  1. Environment Variables:
    • EMBEDDING_MODEL: Path or name of the embedding model (default: sentence-transformers/all-MiniLM-L6-v2).
    • KRONOS_MODEL_PATH: Optional path to override model loading.

Dependencies

  • torch
  • transformers
  • sentence-transformers
  • pandas
  • numpy
  • scikit-learn